Our publications
Selected Peer-Reviewed Journal Publications
Our publications
Sugar kelp application for sustainable potato production in Prince Edward Island: Impacts on soil, greenhouse gas emissions, and yield
Time-of-flight-based advanced surface reconstruction methods for real-time volume estimation of bulk harvested wild blueberries
Using Drones to Predict Degradation of Surface Drainage on Agricultural Fields: A Case Study of the Atlantic Dykelands
Optimizing data collection requirements for machine learning models in wild blueberry automation through the application of DALL-E 2
Exploiting 2D Neural Network Frameworks for 3D Segmentation Through Depth Map Analytics of Harvested Wild Blueberries (Vaccinium angustifolium Ait.)
Leveraging Zero-Shot Detection Mechanisms to Accelerate Image Annotation for Machine Learning in Wild Blueberry (Vaccinium angustifolium Ait.)
Development of a novel precision applicator for spot treatment of granular agrochemical in wild blueberry
MacEachern, C. B., T. J. Esau, Q. U. Zaman, S. N. White, & A. A. Farooque. 2024. Development of a novel precision applicator for spot treatment of granular agrochemical in wild blueberry. Scientific Reports (Nature) 14(13751). doi.org/10.1038/s41598-024-64650-z
Enhancing surface drainage mapping in eastern Canada with deep learning applied to LiDAR-derived elevation data
Bilodeau, M. F., T. J. Esau, Q.U. Zaman, B. Heung, & A. A. Farooque. 2024. Enhancing surface drainage mapping in eastern Canada with deep learning applied to LiDAR-derived elevation data. Scientific Reports (Nature) 14(10016). doi.org/10.1038/s41598-024-60525-5
Evaluation of dichlobenil for hair fescue (Festuca filiformis Pourr.) management in wild blueberry (Vaccinium angustifolium Ait.)
MacEachern, C. B, T. J. Esau, S.N. White, Q.U. Zaman, & A. A. Farooque. 2024. Evaluation of dichlobenil for hair fescue (Festuca filiformis Pourr.) management in wild blueberry (Vaccinium angustifolium Ait.). Agronomy Journal 116:590-597. doi.org/10.1002/agj2.21548
Deep learning supported machine vision system to precisely automate the wild blueberry harvester header
Haydar, Z., T. J. Esau, A. A. Farooque, Q.U. Zaman, P.J. Hennessy, K. Singh, & F. Abbas. 2023. Deep learning supported machine vision system to precisely automate the wild blueberry harvester header. Scientific Reports (Nature) 13(10198). doi.org/10.1038/s41598-023-37087-z
Artificial intelligence and deep learning applications for agriculture
Assessing the effect of machine automation on operator heart and breathing
rate during mechanical harvesting of wild blueberries
MacEachern, C.B., T. J. Esau, Q.U. Zaman, A. A. Farooque. 2023. Assessing the effect of machine automation on operator heart and breathing rate during mechanical harvesting of wild blueberries. Smart Agricultural Technology 4(100171). doi.org/10.1016/j.atech.2023.100171
Machine vision system for real-time debris detection on mechanical wild blueberry harvesters
Das, A.K., T. J. Esau, Q.U. Zaman, A. A. Farooque, A. W. Schumann, & P.J. Hennessy. 2022. Machine vision system for real-time debris detection on mechanical wild blueberry harvesters. Smart Agricultural Technology 4(100166). doi.org/10.1016/j.atech.2022.100166
Identifying hair fescue in wild blueberry fields using drone images for precise application of granular herbicide
Bilodeau, M.F., T. J. Esau, C.B. MacEachern, A. A. Farooque, S. N. White, & Q.U. Zaman. 2022. Identifying hair fescue in wild blueberry fields using drone images for precise application of granular herbicide. Smart Agricultural Technology. doi.org/10.1016/j.atech.2022.100127
Detection of fruit maturity stage and yield estimation in wild blueberry using deep learning convolutional neural networks
MacEachern, C.B., T.J. Esau, A.W. Schumann, P.J. Hennessy, & Q.U. Zaman. 2022. Detection of fruit maturity stage and yield estimation in wild blueberry using deep learning convolutional neural networks. Smart Agricultural Technology. doi.org/10.1016/j.atech.2022.100099
Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms
Usman, A., T.J. Esau, A.A. Farooque, Q.U. Zaman, F. Abbas, & M.F. Bilodeau. 2022. Limiting the Collection of Ground Truth Data for Land Use and Land Cover Maps with Machine Learning Algorithms. International Journal of Geo-Information. doi.org/10.3390/ijgi11060333
Precision of irrigation management using machine learning and digital farming solutions
Application of artificial neural networks to project reference evapotranspiration under climate change scenarios
Evaluation of cameras and image distance for CNN-based weed detection in wild blueberry
Estimation of agricultural dykelands cultivated in Nova Scotia using land property boundaries and crop inventory.
Field capacity and harvest efficiency evaluation of traditional small box and semi-automated bin handling systems for wild blueberry
Comparison of various modelling techniques to estimate land surface temperature: A case study from Prince Edward Island, Canada.
Identification of significant factors affecting potato tuber yield for precision management of soil nutrients
Hair fescue and sheep sorrel identification using deep learning in wild blueberry production
Evaluation of autosteer in rough terrain at low ground speed for commercial wild blueberry harvesting
Detection of a potato disease (early blight) using artificial intelligence
Design and development of a smart variable rate sprayer using deep learning
DropLeaf: a precision farming smartphone tool for real-time quantification of pesticide application coverage
Economic comparison of traditional small box and semi-automatic bin handling harvesting technologies for wild blueberries from a field trial: A stochastic approach
Delineation of management zones for site-specific soil fertility characteristics through proximal sensing of potato fields
Real-time detection of strawberry powdery mildew disease using a mobile machine vision system
Soil and crop variability induced management zones to optimize potato yield
How can potatoes be smartly cultivated with biochar as a soil nutrient amendment technique in Atlantic Canada?
Computation of evapotranspiration with artificial intelligence for precision water resource management
Development and evaluation of a closed-loop control system for automation of a mechanical wild blueberry harvester’s picking reel
Impact of wild blueberry fruit characteristics and machine parameters on performance of a mechanical harvester: basis for automation
Precision irrigation strategies for sustainable water budgeting of potato crop in Prince Edward Island
Estimation of water table depth using DUALEM-2 system
Groundwater estimation from major physical hydrology components using artificial neural networks and deep learning
Forecasting potato tuber yield using soil electromagnetic induction (EMI) method
Economic and management tool for assessing wild blueberry production costs and financial feasibility
Evaluation of DualEM-II sensor for soil moisture content estimation in the potato fields of Atlantic Canada
Development of an artificial cloud lighting condition system using machine vision for strawberry powdery mildew disease detection
Effective use of a variable speed blower fan on a mechanical wild blueberry harvester
Machine vision smart sprayer for spot-application of agrochemical in wild blueberry fields
Machine vision system for real-time debris detection on mechanical wild blueberry harvesters
Das, A.K., T. J. Esau, Q.U. Zaman, A. A. Farooque, A. W. Schumann, & P.J. Hennessy. 2022. Machine vision system for real-time debris detection on mechanical wild blueberry harvesters. Smart Agricultural Technology 4(100166). doi.org/10.1016/j.atech.2022.100166
Machine vision system for real-time debris detection on mechanical wild blueberry harvesters
Das, A.K., T. J. Esau, Q.U. Zaman, A. A. Farooque, A. W. Schumann, & P.J. Hennessy. 2022. Machine vision system for real-time debris detection on mechanical wild blueberry harvesters. Smart Agricultural Technology 4(100166). doi.org/10.1016/j.atech.2022.100166
Machine vision system for real-time debris detection on mechanical wild blueberry harvesters
Das, A.K., T. J. Esau, Q.U. Zaman, A. A. Farooque, A. W. Schumann, & P.J. Hennessy. 2022. Machine vision system for real-time debris detection on mechanical wild blueberry harvesters. Smart Agricultural Technology 4(100166). doi.org/10.1016/j.atech.2022.100166
Machine vision system for real-time debris detection on mechanical wild blueberry harvesters
Das, A.K., T. J. Esau, Q.U. Zaman, A. A. Farooque, A. W. Schumann, & P.J. Hennessy. 2022. Machine vision system for real-time debris detection on mechanical wild blueberry harvesters. Smart Agricultural Technology 4(100166). doi.org/10.1016/j.atech.2022.100166